The unavoidable travel time variability in transportation networks, resulted from the
widespread supply-side and demand-side uncertainties, makes travel time reliability (TTR) …

This paper introduces a new model to identify collective abnormal human behaviors from
large pedestrian data in smart cities. To accurately solve the problem, several algorithms …

This article introduces two new problems related to trajectory outlier detection:(1) group
trajectory outlier (GTO) detection and (2) deviation point detection for both individual and …

Along with urbanization and the deployment of GPS sensors in vehicles and mobile phones,
massive amounts of trajectory data have been generated for city areas. The analysis of …

Many research areas depend on group anomaly detection. The use of group anomaly
detection can maintain and provide security and privacy to the data involved. This research …

Map matching for cellular data is to transform a sequence of cell tower locations to a
trajectory on a road map. It is an essential processing step for many applications, such as …

Predicting how long a trip will take may allow travelers plan ahead, save money, and avoid
traffic congestion. The journey time estimation model should take into account three crucial …

State-of-health (SOH) estimation is crucial for ensuring efficient, reliable and safe operation
of power battery in electric vehicle (EV) application. However, due to the complicated …

Restaurant meal delivery companies have begun to provide customers with meal arrival
time estimations to inform the customers' selection. Accurate estimations increase customer …

Travel Time Estimation (TTE) aims to accurately forecast the expected trip duration from an
origin to a destination. As one of the world's largest ride-hailing platforms, DiDi answers …